A parameterized approximation algorithm for the mixed and windy capacitated arc routing problem: Theory and experiments
We prove that any polynomial‐time α ( n ) ‐approximation algorithm for the n‐vertex metric asymmetric Traveling Salesperson Problem yields a polynomial‐time O ( α ( C ) ) ‐approximation algorithm for the mixed and windy Capacitated Arc Routing Problem, where C is the number of weakly connected compo...
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| Vydáno v: | Networks Ročník 70; číslo 3; s. 262 - 278 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
Wiley Subscription Services, Inc
01.10.2017
|
| Témata: | |
| ISSN: | 0028-3045, 1097-0037 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | We prove that any polynomial‐time
α
(
n
)
‐approximation algorithm for the n‐vertex metric asymmetric Traveling Salesperson Problem yields a polynomial‐time
O
(
α
(
C
)
)
‐approximation algorithm for the mixed and windy Capacitated Arc Routing Problem, where
C
is the number of weakly connected components in the subgraph induced by the positive‐demand arcs—a small number in many applications. In conjunction with known results, we obtain constant‐factor approximations for
C
∈
O
(
log
n
)
and
O
(
log
C
/
log
log
C
)
‐approximations in general. Experiments show that our algorithm, together with several heuristic enhancements, outperforms many previous polynomial‐time heuristics. Finally, since the solution quality achievable in polynomial time appears to mainly depend on C and since C = 1 in almost all benchmark instances, we propose the Ob benchmark set, simulating cities that are divided into several components by a river. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 70(3), 262–278 2017 |
|---|---|
| Bibliografie: | This version describes several algorithmic enhancements, contains an experimental evaluation of our algorithm, and provides a new benchmark data set. A preliminary version of this article appeared in the Proceedings of the 15th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS’15) ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0028-3045 1097-0037 |
| DOI: | 10.1002/net.21742 |